Dense candidate stores [1]}, [2]}, which have similar worst space complexity, only store the data nodes that are potential matches of a given query node. Thus, the space advantage of dense stores is evident when the queries are very selective. They also provide a coalesced memory access while fetching the candidate matches of a query node in contrast to stride access pattern in DEBI. This provides the dense storage approaches an advantage during enumeration. However, updating the dense storage requires searching through multiple key-value stores and each can take \(\mathcal {O}(|V|)\) . In DEBI, we can add, remove and find the entries to be updated in constant time.
